![[Superseded]](figures/lifecycle-superseded.svg)
rename_if(), rename_at(), and rename_all() have been superseded by
rename_with(). The matching select statements have been superseded by the
combination of a select() + rename_with(). Any predicate functions passed
as arguments to select() or rename_with() must be wrapped in where().
These functions were superseded because mutate_if() and friends were
superseded by across(). select_if() and rename_if() already use tidy
selection so they can't be replaced by across() and instead we need a new
function.
Arguments
- .tbl
A
tblobject.- .funs
A function
fun, a purrr style lambda~ fun(.)or a list of either form.- ...
Additional arguments for the function calls in
.funs. These are evaluated only once, with tidy dots support.- .predicate
A predicate function to be applied to the columns or a logical vector. The variables for which
.predicateis or returnsTRUEare selected. This argument is passed torlang::as_function()and thus supports quosure-style lambda functions and strings representing function names.- .vars
A list of columns generated by
vars(), a character vector of column names, a numeric vector of column positions, orNULL.
Examples
mtcars <- as_tibble(mtcars) # for nicer printing
mtcars %>% rename_all(toupper)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# ->
mtcars %>% rename_with(toupper)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# NB: the transformation comes first in rename_with
is_whole <- function(x) all(floor(x) == x)
mtcars %>% rename_if(is_whole, toupper)
#> # A tibble: 32 × 11
#> mpg CYL disp HP drat wt qsec VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# ->
mtcars %>% rename_with(toupper, where(is_whole))
#> # A tibble: 32 × 11
#> mpg CYL disp HP drat wt qsec VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
mtcars %>% rename_at(vars(mpg:hp), toupper)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# ->
mtcars %>% rename_with(toupper, mpg:hp)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# You now must select() and then rename
mtcars %>% select_all(toupper)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# ->
mtcars %>% rename_with(toupper)
#> # A tibble: 32 × 11
#> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# Selection drops unselected variables:
mtcars %>% select_if(is_whole, toupper)
#> # A tibble: 32 × 6
#> CYL HP VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 6 110 0 1 4 4
#> 2 6 110 0 1 4 4
#> 3 4 93 1 1 4 1
#> 4 6 110 1 0 3 1
#> 5 8 175 0 0 3 2
#> 6 6 105 1 0 3 1
#> 7 8 245 0 0 3 4
#> 8 4 62 1 0 4 2
#> 9 4 95 1 0 4 2
#> 10 6 123 1 0 4 4
#> # ℹ 22 more rows
# ->
mtcars %>% select(where(is_whole)) %>% rename_with(toupper)
#> # A tibble: 32 × 6
#> CYL HP VS AM GEAR CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 6 110 0 1 4 4
#> 2 6 110 0 1 4 4
#> 3 4 93 1 1 4 1
#> 4 6 110 1 0 3 1
#> 5 8 175 0 0 3 2
#> 6 6 105 1 0 3 1
#> 7 8 245 0 0 3 4
#> 8 4 62 1 0 4 2
#> 9 4 95 1 0 4 2
#> 10 6 123 1 0 4 4
#> # ℹ 22 more rows
mtcars %>% select_at(vars(-contains("ar"), starts_with("c")), toupper)
#> # A tibble: 32 × 10
#> MPG CYL DISP HP DRAT WT QSEC VS AM CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4
#> # ℹ 22 more rows
# ->
mtcars %>%
select(!contains("ar") | starts_with("c")) %>%
rename_with(toupper)
#> # A tibble: 32 × 10
#> MPG CYL DISP HP DRAT WT QSEC VS AM CARB
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4
#> # ℹ 22 more rows